Econometric Model Research Articles

Economic policy uncertainty and corporate cooperative research and development: Empirical evidence based on Chinese patent data

Based on patent data at the corporate level in China, this paper empirically tests the impact of economic policy uncertainty on corporate cooperative research and development (R&D) by constructing an econometric model. The results reveal that the higher the economic policy uncertainty, the lower the degree of corporate cooperative R&D. Heterogeneity analysis indicates that the negative impact of economic policy uncertainty on corporate cooperative R&D is more pronounced in non-state-owned enterprises and in firms with high financing constraints.

How regulatory media information disclosure affects auditor selection–Empirical evidence based on the interaction platform between investors and listed companies

This study uses a econometric model to assess how online interactions between investors and listed companies influence auditor selection. It observes auditor choice as a metric to gauge management's response to market reactions from information disclosed on investor-company platforms. Findings reveal that more effective online interactions lead to the selection of higher quality auditors, especially in companies with greater marketization and higher institutional investor shareholding ratios.

Impact of technological advancement and greener energy on sustainable agriculture in Asia: Evidence from selected Asian countries

AbstractRegardless of major advancements in food production, Asia continues to confront severe food security challenges. Sustainable agriculture presents entirely new prospects by prioritizing the productive worth of human, social, and natural capital—all of which are abundant in Asian nations or can be replenished at a relatively low financial expense. This paper sets out to explore the role of technological innovation, renewable energy use, financial development, globalization, and institutional quality on the environmental sustainability of agriculture, measured by the greenhouse gas emissions from the agricultural sector for top 10 agricultural economies of Asia from 1990 to 2019. To attain the above objective, we employ a variety of econometric models capable of accounting for cross‐sectional dependence, including the CS‐ARDL model and the Dumitrescu‐Hurlin Panel Granger Causality tests. The result indicates that technological innovation as well as the use of renewable energy can reduce the greenhouse gas emissions from the agricultural sector and thus contribute towards enhancing environmental performance of this sector in short and long run. Although globalization result is revealed to be positive, it turns out to be insignificant in both short and long run. Financial development exerts positive and significant effects on agricultural emissions while the institutional quality is found to be increasing the agricultural environmental performance. Finally, we provide policy recommendations based on the results of the study.

Spatial spillover effect of the enterprise sector on local residents’ income in Vietnam

AbstractThis study uses a panel data set from all 63 provinces in Vietnam and spatial regression models to investigate the spatial spillover effect of the enterprise sector on local residents’ income. The results show that expanding the enterprise sector can directly and indirectly increase local income. Although this spillover effect is positive and significant, it is smaller than the direct effect and gradually diminishes when the distance between provinces increases. For example, the estimation results applying the spatial Durbin model holding other variables constant show that a 10% increase in the enterprise capital volume in Ho Chi Minh City can raise local total income in this city, and first- and second-order neighbours by 0.53%, 0.22%, and 0.17%, respectively. This study provides novel evidence on the spatial spillover effect of the enterprise sector on local incomes using spatial econometric models. The findings offer valuable information for policymakers in planning enterprise sector development to improve local residents’ income in Vietnam.

The effect of provincial policies on seismic disaster mitigation in China: An empirical study.

With the development of earthquake disaster reduction efforts in China, the content of earthquake disaster reduction policies has become increasingly enriched and improved. Particularly, multiple provincial governments have proposed earthquake disaster reduction planning policies. It is important to explore whether these policies can affect disaster mitigation. Therefore, this paper summarizes the earthquake disaster reduction plans and factors influencing seismic resilience. Panel data from 24 provinces between 2012 and 2021 were collected, and a difference-in-differences approach was used to construct an econometric model to evaluate the policy effects and analyze the enhancement of seismic resilience. The results show that the implementation of earthquake disaster reduction policies has a positive impact on earthquake monitoring, evacuation, and emergency relief capabilities, and the estimated policy effects are statistically significant. Moreover, a series of tests were conducted. The conclusions are as follows: (1) Earthquake disaster reduction policies have a positive impact on the improvement of seismic resilience in provinces. (2) Provinces with a higher number of earthquakes experience more significant effects from earthquake disaster reduction policies. (3) Provinces with higher seismic peak ground acceleration values exhibit more pronounced improvements in seismic resilience.

Dynamics of innovation and income inequality mediated by human capital and financial development: a panel data study of Asia-Pacific countries

ABSTRACT Income inequality is one of the most important among the grand challenges faced by the global economy. The hyper-globalization phase and rising digital innovations have accentuated income inequalities within countries. Asia-Pacific countries have shown a continuous rise of income inequalities and surge of innovations. This study attempts to examine the relationship between income inequality and innovation mediated by human development and financialization. For unravelling the dynamics of income inequality, impact of innovation, human capital and financial development of 15 Asia-Pacific countries covering the period 1990–2022 are examined. It employs panel cointegration econometric models for empirical estimation. Findings revealed that innovation has a significant adverse impact on income distribution. Human capital as a mediating variable of innovations has reduced income inequalities, whereas financial development widens income inequalities. Important finding of the study is that the income dis-equalizing effect of financial development outweighs the income equalizing effect of human capital in the presence of improved technological innovations. Public policy lesson emerged from this study is that the policymakers should enact those policies that foster technological innovations with expansion of human development, inclusive financial development, institutional quality and enhancement of macroeconomic stability that can ensure reduction of income inequality.

Unraveling the impact of energy demand and exports on environment and economy: A case study of South Asian Economies

<p class="MsoNormal" style="margin-top: 10pt; text-align: justify;"><span lang="EN-US" style="font-family: 'times new roman', times, serif; font-size: 14pt;">This study employs empirical analysis using an econometric model that examines the interdependence among environmental degradation, exports, and economic development with energy use. It also provides an environmental Kuznets curve (EKC) for selected South Asian economies utilizing time-series data. The findings reveal a long-term, stable equilibrium link between energy demand and pollution. There exists a positive relationship between structural factors and pollution. Moreover, this study constructs a model of exports and pollution from an interdependent perspective. The three perspectives are tested: the scale and structure of energy consumption considering the twin constraints of export-trade and pollution, and the scale of pollution in export-trade constraint. These results show that the increase in energy use leads to higher CO2 emissions amidst export volume. However, in the presence of income, the scale of effect lowers a little. The analysis also supports the presence of Kuznets curve for south-Asian economies. The results imply substantial scope for development in the energy use and pollution structure within South Asia's current export trade process. This development can be attained by regulating energy use and enhancing system efficacy without necessitating changes to the scale effect or structural effect.</span></p>

Probit Analysis of Attitudes of Surrounding Farming Communities Towards Urban Expansion: Bishoftu Town, East Shewa Zone, Oromia Regional State

The general objective of the study was to investigate the attitudes of surrounding farming community towards urban expansion and to assess whether they would accept this form of expansion close to their farming land in Bishoftu town. 303 farmers around bishoftu town was interviewed using systematic random sampling method. Yeman’s formula was used to get the appropriate sample. To analyse the data descriptive and econometric method were used. From descriptive percentage and frequency, was employed and probit econometric model was used to analyse determinant factors which affect the perception for urbanization as opportunity or treat. From these six variables where significantly affected the perception of the farmers at different significant level. This are age, level of education housing type, total agricultural produce income, religion, ethnicity and land holding. From this research result it is recommended to provide training for farmers about the importance of urbanization. We must give due attention in the process of urbanization for not affecting the major farm land. And the government of Ethiopia should focus on non-farmable areas in the process of urbanization and urban expansion.

The use of the (Tobit) Model in Studying the Variables affecting the Increase in the Number of People with Systolic Hypertension, in the Presence of the problem of Heterogeneity of Random Error Variance

The process of regression analysis is based on a number of basic assumptions, and if one of these assumptions is not available, this will lead to obtaining inaccurate results, and the most of these assumptions is homoscedasticity, violating this assumption causes a problem of heteroscedasticity of the random error variance the, which may come from different variances This cause to misleading and inaccurate decisions. Recently Econometric models received attention, especially limited regression models, which contain specific response variables and several repeated observations within a certain range, including Tobit models and also considered imitations of the Censored Regression Model. Problem arise when it appears in the data heteroscedasticity, which makes methods of estimating the parameters of the linear regression model giving incorrect and inaccurate results, hence we get Biased parameters that do not have minimalist variance, as well as getting an unreliable p-value. The objective of this research is to study the estimation of the multiple standard (TOBIT) model which features that the variable (Y) specific variant. In heteroscedasticity, which both likelihood function method weighted and Genetic Algorithm was used in simulation. To sum up, the results showed, that Genetic algorithm better outcomes than weighted likelihood function method therefore, it was used in the practical application.

Liner shipping connectivity: A dynamic link between energy trade, green exchange and inclusive growth using advanced econometric modelling

The ocean economy is crucial in facilitating green exchanges and promoting inclusive growth. Despite its significance, this domain needs more investigation, leading to diverse findings in existing literature. This study empirically examines the links between energy trade, green exchanges, and inclusive growth within the context of the ocean economy in the Belt and Road Initiative (BRI) region. Using the Liner Shipping Connectivity Index as a proxy for ocean economy and debt-for-nature swaps as a proxy for green exchanges, we employ an advanced Two-Step System of GMM econometric modelling. Data from 23 BRI member countries, sourced from WDI (World Bank), OECD Statistics, and UNCTAD Statistics, covering the period from 2004 to 2022, form the basis of our analysis. Our findings confirm a long-run dynamic relationship between the ocean economy, energy trade, green exchanges, and inclusive growth. The results indicate that the ocean economy and debt-for-nature swap financing contribute to economic growth. However, results show a weak marine structural development because the results are not highly significant. To address this, we propose comprehensive policy measures to strengthen structural development to enhance inclusive economic growth. Our study highlights the need for strategic policies that balance economic benefits with sustainability goals, leveraging technological advancements and promoting equitable growth.

Investigating Economic and Climate Signals in Groundwater Data

Hydrologic, climatic, regulatory and economic factors interact in complex ways to influence groundwater conditions. These relationships can be difficult to measure and model but are important for water management and for considering viable futures for regional economies. This paper proposes a strategy for an improved understanding of how groundwater levels reflect signals of regulatory, economic and climate factors. Most existing econometric studies of groundwater use focus on large-scale irrigated agriculture and urbanized areas in first world nations, where groundwater extraction data is available. In much of the world, groundwater extraction data are not available for individual farms and other water users. The goal of this study is to explore the responsiveness of groundwater levels (a more widely available measure of groundwater conditions) to regulatory, economic and climate signals in rural areas, using a growing body of remotely sensed land cover data. Pooled Ordinary Least Squares econometric models examine the effects of regulatory, climatic and economic factors on groundwater levels in rural Arizona. Groundwater regulations, recharge projects, housing units and irrigated acreage have statistically significant relationships to groundwater levels in the study areas. This approach can be valuable for understanding factors that influence groundwater conditions and which may be useful in managing groundwater use in widespread areas where groundwater extraction data is unavailable.

ECONOMETRIC MODELS FOR ASSESSING FINANCIAL SUSTAINABILITY IN THE ERA OF DIGITAL INNOVATION

The article proposes to use econometric models to analyze factors affecting financial stability in the new digital economy. Based on empirical evidence, the authors explore the impact of digital innovation on the financial system, identify key factors that determine the level of financial sustainability, and make recommendations for improving financial stability management in the new digital format.

A user-friendly method for estimating discrete choice land-use model in a panel data setting

Land-use modeling stands as a pivotal tool in shaping sustainable development policies. With the rapid advancement of remote-sensing technology and the widespread adoption of satellite imagery-based land cover products, these datasets have emerged as primary sources for understanding land-use dynamics due to their high spatial and temporal resolutions. Yet, it remains challenging to effectively integrate such rich panel data into nonlinear econometric land-use models. This paper introduces a method to seamlessly incorporate land cover panel data into econometric models, enabling comprehensive utilization of temporal information within a single framework.-By capturing dynamic land-use patterns, the method enhances prediction accuracy while mitigating issues such as autocorrelated error terms commonly encountered in panel data analysis.-The method is straightforward to implement and applicable to many nonlinear models, making it particularly suitable for datasets with large sample sizes.

Investigation of the Relationship between Women Indicators and Socio-Economic Development Index using Spatial Econometrics Models

Investigation of the Relationship between Women Indicators and Socio-Economic Development Index using Spatial Econometrics Models

Developing Economic and Mathematic Models of Company Tax Burden Taking into Account Specific Features of Industry

The importance and appraisal of enterprise tax burden is underlined by its serious impact on its finance and business functioning. In order to conduct a high-quality tax controlling, cut tax risks and achieve optimal tax burden the author focuses attention on studying theoretical principles and approaches to estimating the impact of tax burden on business activity of the organization. Through analyzing economic and mathematic methods of assessing company tax burden elaborated by Russian scientists, focus was made on the importance of investigating this indicator within the frames of econometric modeling with the help of language R. To estimate the impact of tax burden on results of business activity and finance and economic factor on the amount of tax burden the article proposed to build models with panel data, whose shaping can help identify steps aimed at upgrading tax control and tax burden management.

Economic crisis, urban structural change and inter-sectoral labour mobility

Are recessions drivers of structural change? Here we investigate employment dynamics in the UK and show that a re-allocation of labour between industrial sectors in times of crisis induces an acceleration in structural change. Our key hypothesis is that cities with industrial baskets that exhibit strong potential for inter-industry labour mobility are more resilient as they can shift workers between sectors resulting in employment growth in some sectors — which in turn induces structural change during an economic crisis. Probing this hypothesis, we find that UK cities experienced a sharp increase in the rate of structural change at the city level around 2009 which coincided with an increase in inter-sectoral job transitions during the recession (2008–11) which persisted for years afterwards. To shed light on this, we deploy an econometric model to show that local employment in skill-related sectors, which captures the potential for inter-industry labour mobility, is most strongly associated with city-industry employment growth during the recession period.

A multiscale time-series decomposition learning for crude oil price forecasting

Crude oil price forecasting is important for market participants and policymakers. However, accurately tracking oil prices is quite a challenging task due to the complexity of temporal oil data and the nonlinear relationships involved in the forecasting task. In this study, a multiscale time-series decomposition learning framework is proposed to deal with this issue. First, a multiscale temporal processing module is designed to capture different frequency time-series patterns in historical data at various scales. Then, a multiscale decomposition technique is applied to decompose historical crude oil data into various temporal modes, involving global shared information across multiple scales, as well as local specific information that varies at each scale. Finally, a multiscale fusion mechanism is employed to combine these information, which are further used as inputs to construct nonlinear and complex predictive models for crude oil prices. A series of experiments conducted on Shanghai crude oil market demonstrate that the proposed approach outperforms several econometric and machine learning models.

The impact of the digital economy on environmental pollution: a perspective on collaborative governance between government and Public

The rapid development of the digital economy is driving transformative changes in a multifaceted collaborative environmental governance system. From the perspective of collaborative governance between government and the public, this study employs double fixed-effects models, spatial econometric models, and instrumental variables methods to empirically explore how the digital economy influences environmental pollution, using panel data from 30 provinces in China spanning 2011 to 2022. The results demonstrate that the digital economy significantly lowers environmental pollution. The primary mechanism is through the government’s environmental governance behaviors, which are positively moderated by public environmental concerns, enhancing effectiveness. Additionally, the digital economy induces a spatial spillover effect on environmental pollution. This promotion of collaborative management between the government and the public is poised to become a pivotal direction in future environmental governance.

Exchange Policy and Misalignments in Morocco: A Quantitative Analysis

The research examines the equilibrium exchange rate and misalignment quantifications for the case of Morocco over the period 1990-2022. Based on an econometric model developed by Edwards in 1994, fundamental variables such as productivity, foreign direct investment (FDI), inflation and the real interest rate (RIR) are analysed to estimate the equilibrium value of the real exchange rate (REER) of the Moroccan dirham. The results show a cointegration between the REER and the fundamental variables, indicating the existence of a long-term relationship. The analysis of misalignments reveals periods of overvaluation and undervaluation of the Moroccan dirham, influenced by economic factors and monetary policies. This study has important implications for economic and monetary policy in Morocco, particularly with regard to export competitiveness and macroeconomic stability.

Economic upgrading of Central and Eastern European economies through global value chain participation and foreign direct investment

ABSTRACT This paper links global value chain (GVC) integration and operations of multinational enterprises (MNEs) in the context of host economies upgrading. Economic upgrading is referred to as higher exported value added that has been generated in the domestic economy as a result of foreign direct investment (FDI). Particular attention is paid to the impact of GVC on selected Central and Eastern European (CEE) economies. An econometric model is estimated using panel data of 44 sectors for four CEE economies over the period 1995–2018. A primary source of data is the latest edition of the TiVA (Trade in Value Added). The most important variable in explaining domestic contribution to GVC was the flow of foreign inputs. Backward linkages are crucial for building the GVC presence of the economies. The variables of interest – FDI stocks and flows – have in general a negative impact on the level of domestic content in analysed economies.